Water Stress Management Based on Groundwater Depletion Estimation in Saudi Arabia: A Hybrid ARIMA-GLS Approach

Water Stress Management Based on Groundwater Depletion Estimation in Saudi Arabia: A Hybrid ARIMA-GLS Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Water Stress Management Based on Groundwater Depletion Estimation in Saudi Arabia: A Hybrid ARIMA-GLS Approach Sani Abba, Syed Muzzamil Hussain Shah, Mohamed A. Yassin, Sagiru Mati, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3893996/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Water scarcity is a pressing global challenge, and arid regions like Saudi Arabia face the urgent need for effective water stress management. The current study proposes an innovative method to tackle this issue by utilizing a hybrid time series analysis model, comprising of Autoregressive Integrated Moving Average (ARIMA) and Generalized Least Squares (GLS) techniques to estimate groundwater depletion trends in Saudi Arabia. The research employs historical groundwater data, climatic variables, and socioeconomic indicators to formulate comprehensive insight of the factors influencing groundwater depletion. The ARIMA component of the hybrid model captures the temporal dynamics of groundwater levels, while GLS considers the spatial and cross-correlation dependencies among observation points, enhancing the accuracy of depletion estimates. The study also demonstrates the significance of climatic variability and socioeconomic factors in exacerbating water stress in the region. Furthermore, the hybrid ARIMA-GLS model offers a robust tool for forecasting future groundwater depletion trends, aiding proactive decision-making in mitigating water stress. The numerical results for different wells proved to be essential in assessing the Mean Absolute Percent Error (MAPE). For instance, the MAPE values were found to be as (i) hybrid ARIMA-CLS (MAPE = 0.1507), (ii) ARIMA-CLS (MAPE = 0.429834), (iii) ARIMA-CLS (MAPE = 0.109115) for 4-H-84-N, 4-H-86-U, 4-S-316-U, respectively with the expectation of (iv) ARI (MAPE = 6.0285) for DA-45-U well. It is therefore believed that this research contributes to the broader discussion on managing the water resource in arid regions and highlights the significance of integrated approaches that consider both temporal and spatial dimensions. Further, it offers valuable insights and a practical framework for addressing water stress challenges in Saudi Arabia and serves as a model for water management in other arid regions grappling with similar issues. Physical sciences/Engineering Earth and environmental sciences/Climate sciences/Hydrology Water security regression model hybrid model groundwater Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3893996","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":273313266,"identity":"1ed42a36-ff12-447b-9eb7-42625a137a4b","order_by":0,"name":"Sani Abba","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIiWNgGAWjYJCCA0CUwMDexvABwk8gVgvPMcYZRGthAGuRSCNSi3z72YMHGGru5PHPfJbYzLtjGwM/e44B448a3FoMzuQlHGA49qxY4nbawWbeM7cZJHveGDDzHMOjhSHH4AAD2+HEhtvp7Y95224zGNzIMWBmYMPjsP43QC3/DifOv3m8sRmkxf4GyGH/8HgGqOAAY9vhxA032A6CtRhI5Bgw8LbhcdgNoC2Jfc+KDc+kJTbOPXObR+LMs4LDvH34HJZj/OHDtzt5csePGTa83XFbjr89eePDH9/wOAwEEmAMxgYGHhB9gIAGJADUMgpGwSgYBaMAAwAADLReXxlb/YYAAAAASUVORK5CYII=","orcid":"","institution":"King Fahd University of Petroleum and Minerals Dhahran 31261","correspondingAuthor":true,"prefix":"","firstName":"Sani","middleName":"","lastName":"Abba","suffix":""},{"id":273313267,"identity":"ce26b831-390d-4397-b186-e1ea2b90482a","order_by":1,"name":"Syed Muzzamil Hussain Shah","email":"","orcid":"","institution":"King Fahd University of Petroleum and Minerals Dhahran 31261","correspondingAuthor":false,"prefix":"","firstName":"Syed","middleName":"Muzzamil Hussain","lastName":"Shah","suffix":""},{"id":273313268,"identity":"8f60d180-2e1b-48d6-9d27-db0c649262d0","order_by":2,"name":"Mohamed A. 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The current study proposes an innovative method to tackle this issue by utilizing a hybrid time series analysis model, comprising of Autoregressive Integrated Moving Average (ARIMA) and Generalized Least Squares (GLS) techniques to estimate groundwater depletion trends in Saudi Arabia. The research employs historical groundwater data, climatic variables, and socioeconomic indicators to formulate comprehensive insight of the factors influencing groundwater depletion. The ARIMA component of the hybrid model captures the temporal dynamics of groundwater levels, while GLS considers the spatial and cross-correlation dependencies among observation points, enhancing the accuracy of depletion estimates. The study also demonstrates the significance of climatic variability and socioeconomic factors in exacerbating water stress in the region. Furthermore, the hybrid ARIMA-GLS model offers a robust tool for forecasting future groundwater depletion trends, aiding proactive decision-making in mitigating water stress. The numerical results for different wells proved to be essential in assessing the Mean Absolute Percent Error (MAPE). For instance, the MAPE values were found to be as (i) hybrid ARIMA-CLS (MAPE\u0026thinsp;=\u0026thinsp;0.1507), (ii) ARIMA-CLS (MAPE\u0026thinsp;=\u0026thinsp;0.429834), (iii) ARIMA-CLS (MAPE\u0026thinsp;=\u0026thinsp;0.109115) for 4-H-84-N, 4-H-86-U, 4-S-316-U, respectively with the expectation of (iv) ARI (MAPE\u0026thinsp;=\u0026thinsp;6.0285) for DA-45-U well. It is therefore believed that this research contributes to the broader discussion on managing the water resource in arid regions and highlights the significance of integrated approaches that consider both temporal and spatial dimensions. Further, it offers valuable insights and a practical framework for addressing water stress challenges in Saudi Arabia and serves as a model for water management in other arid regions grappling with similar issues.\u003c/p\u003e","manuscriptTitle":"Water Stress Management Based on Groundwater Depletion Estimation in Saudi Arabia: A Hybrid ARIMA-GLS Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-19 20:13:20","doi":"10.21203/rs.3.rs-3893996/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ee3dac31-865f-4ef6-9b2c-8eaeaac610a4","owner":[],"postedDate":"February 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28813043,"name":"Physical sciences/Engineering"},{"id":28813044,"name":"Earth and environmental sciences/Climate sciences/Hydrology"}],"tags":[],"updatedAt":"2024-07-17T06:24:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-19 20:13:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3893996","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3893996","identity":"rs-3893996","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}